title: Compression-ratio-based seizure detection.
abstract: For wireless seizure monitoring devices seizure detection and data compression are two critical tasks that need to be carefully designed against a very tight power budget to maximize the battery life. These two tasks are usually considered separately and algorithms for each are developed separately. In this paper, we consider having a single low-power algorithm for implementing both seizure detection and data compression. Towards that end, we investigated compression ratio (CR) as a seizure marker and show that the seizure detection can be achieved as a by-product of compression with no additional cost, and thus overall system power can be reduced. We show that the proposed method, the CR-based seizure detection has promising performance with 88% seizure detection accuracy, and 5.5 false positives per hour (FPh) without any computation overhead.
authors.forename: Chung-Lin
authors.initials: CL
authors.lastname: Sha
authors.forename: Taehoon
authors.initials: T
authors.lastname: Kim
authors.forename: N Sertac
authors.initials: NS
authors.lastname: Artan
authors.forename: H Jonathan
authors.initials: HJ
authors.lastname: Chao
mesh_terms: D000465:Algorithms; D044962:Data Compression; D004569:Electroencephalography; D006801:Humans; D012640:Seizures / Q000175:diagnosis*